The statement “If there is sufficient evidence to reject a null hypothesis at the 10% significance level, then there is sufficient evidence to reject it at the 5% significance level” is: Please select the best answer of those provided below.
Question
The statement “If there is sufficient evidence to reject a null hypothesis at the 10% significance level, then there is sufficient evidence to reject it at the 5% significance level” is: Please select the best answer of those provided below.
Solution
The statement is False. The level of significance is the probability of rejecting the null hypothesis if it is true. A lower significance level means that you require stronger evidence to reject the null hypothesis. So, if there is sufficient evidence to reject a null hypothesis at the 10% significance level, it does not necessarily mean that there is sufficient evidence to reject it at the 5% significance level.
Similar Questions
Everything else remaining the same, is it easier to reject a null hypothesis with a 5% or 1% level of significance?
If we reject a null hypothesis at the 0.05 level of significance, then we must also reject it at the 0.10 level.Group of answer choicesTrueFalse
Significance LevelLet’s suppose that for a particular test, you have been able to reject the null hypothesis at 5% significance level. Can you reject the null hypothesis for the same test at 10% significance level?YesNoCannot be said
If a hypothesis is not rejected at a 5% level of significance, it will ___.Group of answer choicesalso not be rejected at the 1% levelalways be rejected at the 1% levelsometimes be rejected at the 1% levelNot enough information is given to answer this question
Perform an A/B testWhich of the following statements is true?You can reject the null hypothesis while testing at a 20% significance level but not at 10%.You can reject the null hypothesis while testing at a 10% significance level but not at 5%.You can reject the null hypothesis while testing at a 5% significance level but not at 1%.You can reject the null hypothesis while testing at a 1% significance level.
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